Object tracking finds its application in several computer vision applications, such as video compression, surveillance, robotics etc. Moving object detection and tracking are important steps in object recognition, context analysis and indexing processes for visual surveillance systems. It is a big challenge for researchers to make a decision on which tracking algorithm is more suitable for whic...

Object tracking is commonly used in video surveillance, but typically video with full frame rate is sent. We previously have shown that full frame rate is not needed, but it is unclear what the appropriate frame rate to send or whether we can further reduce the frame rate. This paper answers these questions for two commonly used object tracking algorithms (frame-differencing-based blob tracking...

Moving object detection, classification and tracking are more crucial challenging task in most of the computer vision machine applications such as robot navigation, human behavior analysis, traffic flow analysis etc. However, detection algorithms not suitable for real time processing causes slower speed due to analyzing high resolution video from high-end multiple cameras. It requires computati...

Local feature based object tracking approaches have been promising in solving the tracking problems such as occlusions and illumination variations. However, existing approaches typically model feature variations using prototypes, and this discrete representation cannot capture the gradual changing property of local appearance. In this paper, we propose to model each local feature as a feature m...